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Restoration priorities for Caatinga dry forests: landscape resilience, connectivity and biodiversity value

Citation

Antongiovanni, Marina et al. (2022), Restoration priorities for Caatinga dry forests: landscape resilience, connectivity and biodiversity value, Dryad, Dataset, https://doi.org/10.5061/dryad.cvdncjt60

Abstract

1. Restoration actions can halt biodiversity loss and rescue its services. However, in order to be effective, priority areas for restoration should be chosen based on objective large-scale restoration planning. Here, a multi-criteria graph theory (GT) framework is proposed to indicate priority areas for active restoration, based on landscape resilience, landscape connectivity, and biodiversity conservation value, focusing on threatened endemic plant species.

2. We applied this GT framework to 10,406 catchment basins of the Brazilian Caatinga, the largest seasonally dry tropical forest of the New World. Vegetation cover and within-catchment connectivity were used to identify catchments of intermediate landscape resilience, which in principle offer more effective opportunities for restoration. Then, such catchments were independently classified into (i) three classes according their value for between-catchment connectivity and (ii) three classes of biodiversity conservation value, based on richness of threatened, endemic plant species. By the integration of landscape resilience, landscape connectivity and biodiversity conservation values, three priority classes for restoration were generated.

3. The multi-criteria framework generated several restoration priority cut-offs. Prioritization based on landscape resilience selected 36% of the Caatinga catchments as high priority for restoration. By independently adding landscape connectivity and biodiversity conservation value, only 12% and 3% of the catchments, respectively, were considered high priority. By combining all three criteria, 9% of the catchments were selected as high priority and less than 1% as top priority for restoration.

4. Synthesis and applications: The multicriteria GT framework for restoration prioritization, which maximizes the effectiveness of restoration actions, landscape connectivity for climate change adaptation and conservation of threatened species, can be applied worldwide under different budged limitations and spatial scales, being useful for private, state, and federal initiatives.

Methods

The 2009 Caatinga vegetation cover map used as the basis of this work. It was he national official data, in that occasion, and was made available as georeferenced digital files (shapefiles) in 2014 by the Satellite Deforestation Monitoring Project (PMDBBS) of the Brazilian Ministry of Environment (MMA). Another database of this work was the water catchment basin, delimited by the authors using ArcHydro 2.0 module for ArcGis® 10.1 based on SRTM dataset (version 4 - http://srtm.csi.cgiar.org/). To improve the solution, the original SRTM raster file was reconditioned using as reference the digitized drainage vector layer from Instituto Brasileiro de Geografia e Estatística (IBGE) at 1:250,000 scale. Sub basin grids with threshold of 7,500 ha were created for the entire Caatinga region using the flow direction grid, segmented stream grids developed at this scale, and the Hydro Tools “catchment grid delineation” tool. These sub-basin grids were then converted into separate polygon shapefiles using the Hydro Tools “catchment polygon processing” tool. The detailed description of the data source and the bases derivation are described in Antongiovanni et al. accepted to be published in Journal of Applied Ecology. The detailed description of the variables used in this dataset and how they were generated are also avaiable in the metadata below.

Usage Notes

The detailed description of the variables used in this dataset and how they were generated are in the table below.

Variable Description
ID Identifier
ID_text Identifier (in text format)
Area_ha Catchment basin area (hectares). Catchment basins were delimited using ArcHydro 2.0 module for ArcGis® 10.1 based on SRTM dataset (version 4 - http://srtm.csi.cgiar.org/). To improve the solution, the original SRTM raster file was reconditioned using as reference the digitized drainage vector layer from Instituto Brasileiro de Geografia e Estatística (IBGE) at 1:250,000 scale. Sub basin grids with threshold of 7,500 ha were created for the entire Caatinga region using the flow direction grid, segmented stream grids developed at this scale, and the Hydro Tools “catchment grid delineation” tool. These sub-basin grids were then converted into separate polygon shapefiles using the Hydro Tools “catchment polygon processing” tool.
nfrags Number of fragments. The 2009 Caatinga vegetation cover map used as the basis of this work was made available as georeferenced digital files (shapefiles) in 2014 by the Satellite Deforestation Monitoring Project (PMDBBS) of the Brazilian Ministry of Environment (MMA), the national official data in that occasion. Remnant areas ≤ 1 ha were excluded from the analysis, given the high probability of errors in these very small areas
area_veg Remaining Caatinga vegetation area (hectares) in 2009. Caatinga vegetation cover map used as the basis of this work was made available as georeferenced digital files (shapefiles) in 2014 by the Satellite Deforestation Monitoring Project (PMDBBS) of the Brazilian Ministry of Environment (MMA), the national official data. Furthermore, we also excluded areas within buffers of 220 m and 120 m around paved and unpaved roads of an official road shapefile (IBGE, 2010), since many of those areas are well disturbed.
pct_veg Remaining Caatinga vegetation area (percentage) in 2009.
PC_divarea Catchments basin internal connectivity divided by catchment basin area. Internal connectivity were calculated based on graph theory (Bunn et al., 2000; Urban and Keitt, 2001). For each catchment basin a graph is built, where habitat patches are represented as nodes and functional links among them are represented by connections. Functional link represents the potential displacement of individuals between two habitat patches while the link strength represents the probability of such displacement. The probability of direct displacement between any two patches was considered to be an inverse exponential function of the displacement distance (e.g., Urban and Keitt, 2001; Saura and Pascual-Hortal, 2007). We assumed that a displacement distance of 100 m would lead to a 50% decrease in the probability of direct displacement.  
Resilie_ok Resilience classes. Catchments were classified in three classes of resilience level, based on their vegetation cover and among-patch (fragments) connectivity. Catchment basins classified as low resilience were those with 0-20% vegetation cover regardless their PC levels, and those with 20-40% cover and below median PC_divarea values (internal connectivity) for this subset of landscapes. Low resilience catchments were assumed as very low priority for restoration since in such environmental context restoration actions are less efficient and more costly. Catchments classified as high resilience were those with 80-100% vegetation cover, independent of their PC levels, and those with 60-80% cover but PC levels equal to or higher than the median for this subset of landscapes. High resilience catchments were also assumed as very low priority for restoration because their integrity imply that they have adequate conditions for maintaining their biodiversity and regenerate though natural successional processes. Thus, in principle, they do not require investment in restoration. Intermediate resilience catchment basins were those with (a) 20-40% cover and PC values equal to or higher than the median for this subset of landscapes, (b) 40-60% cover regardless PC levels, and (c) 60-80% cover and PC values lower than the median for this subset of landscapes.
varIICflux varIICflux is an index that measures the estimated amount of dispersal flow from a given node (or catchment basin) to adjacent nodes (Bodin and Saura, 2010; Saura and Rubio, 2010). This variable was calculated just for catchment basins of interediate resilience.
varIICconn varIICconn is an index that measures the relative contribution of a node (or catchment basin) as a stepping stone between two or more nodes adjacent to it  (Bodin and Saura, 2010; Saura and Rubio, 2010). This variable was calculated just for catchment basins of interediate resilience.
norIICflux Standardization of varIICflux  index from 0 to 1. This variable was calculated just for catchment basins of interediate resilience.
norIICcone Standardization of varIICconnector  index from 0 to 1. This variable was calculated just for catchment basins of interediate resilience.
Prior_norm Connectivity value of each intermediate resilience catchment. It was obtained by the sum of standardized values of vardIICflux and vardIICconnector. Thus, the connectivity value potentially varied from 0 to 2. This variable was calculated just for catchment basins of interediate resilience.
Conn_value External connectivity value (CV). This variable was calculated just for catchment basins of interediate resilience.
Sp_richne Number of threatened plant species. The list of Caatinga threatened plant species as well as their geographical distribution were obtained in the Red Book of Brazilian Flora (Martinelli and Moraes, 2013).
Biod_value Biodiversity conservation value (BV) classes of intermediate resilience catchments. To calculate the classes we use the Sp_richne field. Catchments of low BV have zero species. Medium BV catchments have from 1 to 10 species and high BV catchments have more than 10 species.
Priority Restoration priority classes. This variable was calculated by crossing the classes of the variables Conn_value and Biod_value. Thus, the high priority class comprises the following catchment basins: i) high Conn_value and high Biod_value, ii) high Conn_value and medium Biod_value and iii) high Biod_value and medium Conn_value. The catchment basins were considered as medium priority when Conn_ Value and Biod_value were medium. Finally, catchment basins were considered low priority when: i) Conn_value and Biod_value are low, ii) Conn_value is medium and Biod_value is low and iii) Biod_value is medium and Conn_value is low.
Clas_paper This field contains informations from Resilie_ok and Priority fields grouped together.

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: 308040/2017-1

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: 305304/2013-5